Enhanced Dynamic Programming for Polygonal Approximation of ECG Signals

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9 Scopus citations

Abstract

Polygonal approximation is suitable for expressing ECG signal with a few vertices, and it is possible to reliably detect the fiducial point by emphasizing the feature values of the fiducial point. However, there are difficulties in real time processing due to the time and space complexity of dynamic programming step. In this paper, based on the features of polygonal approximation in ECG signal, the dynamic programming is possible to realtime processing through the improvement of three-step, and it is confirmed that advanced polygonal approximation is possibility of signal compression.

Original languageEnglish
Title of host publicationLifeTech 2020 - 2020 IEEE 2nd Global Conference on Life Sciences and Technologies
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages121-122
Number of pages2
ISBN (Electronic)9781728170633
DOIs
StatePublished - Mar 2020
Event2nd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2020 - Kyoto, Japan
Duration: 10 Mar 202012 Mar 2020

Publication series

NameLifeTech 2020 - 2020 IEEE 2nd Global Conference on Life Sciences and Technologies

Conference

Conference2nd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2020
Country/TerritoryJapan
CityKyoto
Period10/03/2012/03/20

Keywords

  • dynamic programming
  • ECG
  • optimization
  • polygonal approximation
  • signal compression

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